Ai Data Developer Jobs in Renton, WA (NOW HIRING)

Requirement - AI Data Engineer

Location- Redmond WA 98052-Hybrid

Contract W2

Top 3 Must-Have Hard Skills

1. Reporting & Analytics – 5+ Years

• Minimum 5 years of experience designing and developing reporting and analytics solutions.
• Hands-on expertise with Power BI, Data Modeling, and DAX.
• Experience with Grafana or similar reporting/dashboard platforms.
• Ability to develop and maintain HTML/web-based reports.

2. Automation, AI & Agentic Solutions – 3+ Years

• Minimum 3 years of experience in automation and AI-driven engineering solutions.
• Strong programming skills in Python, C#, and PowerShell.
• Experience with AI-assisted engineering tools, Copilot/Agentic platforms, and automated report generation.

3. Data Engineering – 5+ Years

• Minimum 5 years of experience in data engineering and data integration.
• Strong proficiency in SQL, ETL processes, and data pipeline development.

Typical Day in the Role

• Purpose of the Team: The purpose of this team is to provide telemetry reporting, analytics, automation, and AI-driven insights that improve visibility into service health, availability, and operational performance through dashboards, reporting solutions, and data engineering capabilities.
• Key projects: This role will contribute to telemetry and service health initiatives by developing reporting, analytics, and automation solutions. Responsibilities include building Power BI reports and Grafana dashboards, creating Kusto-based analytics, supporting telemetry monitoring, and improving data-driven insights related to availability and operational health.

Candidate Requirements

• Disqualifiers: Candidates with limited or no experience in reporting and analytics, automation, AI-assisted solutions, data engineering, Power BI, Grafana, or Kusto-based data analysis will not be eligible for the role.
• Best vs. Average: The ideal resume will contain hands-on experience with telemetry and analytics platforms, including Power BI, Grafana, SQL/Kusto, Python, PowerShell, or C#, along with expertise in data engineering, ETL/data pipelines, automation, and AI-assisted reporting solutions. Experience supporting telemetry health, availability monitoring, operational dashboards, and enterprise-scale reporting environments is highly preferred.

Description

The main function of an AI Data Engineer is to design, develop, enhance, validate, maintain, and support telemetry reporting, data solutions, automation, and AI-assisted solutions. The role develops reports, dashboards, data models, automation, reporting & analytics agent components, and supporting data solutions to improve telemetry coverage, telemetry availability, clean telemetry, and telemetry data quality.

Job Responsibilities

• Design, develop, and maintain telemetry reporting, data solutions, automation, and AI-assisted solutions.
• Design, develop, and enhance Power BI reports, Grafana dashboards, semantic models, and analytics solutions to deliver actionable business insights.
• Develop and optimize Azure Data Explorer (Kusto/ADX) queries, functions, data models, scheduled tables, materialized tables, snapshot tables, and supporting datasets.
• Integrate enterprise data sources and develop supporting SQL queries, ETL processes, and data pipelines required for analytics and reporting solutions.
• Develop automation solutions using Python, PowerShell, C#, or similar scripting/programming languages to automate operational tasks and support business requirements.
• Develop AI-enabled reporting and analytics agent components, including Copilot Agents, Agency CLI skills, prompt assets, and supporting knowledge files.
• Validate data quality, business logic, report accuracy, dashboards, and scheduled refreshes to ensure reliable production solutions.
• Monitor, troubleshoot, and resolve data pipeline, query, reporting, and production issues to maintain solution reliability and performance.
• Create and maintain technical documentation, reusable components, and engineering best practices to support long-term solution maintainability.
• Collaborate with cross-functional engineering teams to deliver scalable, high-quality analytics and reporting solutions.